Prediction of flow in non prismatic compound open channel using artificial neural network

Abstract

Each river in the world is unique. Some are gently curved, others are meander, and some others are relatively straight and skewed. The size of river geometry also changes from section to section longitudinally due to different hydraulic and surface conditions called non-prismatic channel. Much of the research work are found to be done on prismatic compound channels. There has also been a progress of work found for meandering channels. But an era which has been neglected is that of the work for non-prismatic compound channels. An effort has been made to scrutinize the research work related to non-prismatic channels in different types of flow conditions. An experimental observation has been made to investigate the velocity distribution, boundary shear stress distribution and energy loss of a compound channel with converging flood plain. The calculation of Depth average velocity, energy loss, boundary shear stress in non-prismatic compound channel flow is more complex. The prediction of the flow characteristics in compound channels with prismatic and non-prismatic floodplains is a challenging task for hydraulics engineers due to the three dimensional nature of the flow. Simple conventional approaches cannot predict the above mentioned flow characteristics with sufficient accuracy, hence in this area an easily implementable technique the Artificial Neural Network can be used for prediction, validation and analysis of the flow parameters mentioned. The model performed quite satisfactory when compared with the other conventional methods.